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Manufacturing

Tesla Roadster Battery Longevity Test

By Automotive, Autonomous, Connected, Electric, Shared Vehicles, Manufacturing One Comment

Following the seemingly endless discussions about the “true” range of eclectic vehicle has been fascinating. Remember the New York Times’ article Stalled Out on Tesla’s Electric Highway and the ensuing public back and forth between Elon Musk and John Broder?

There are differing opinions on the range viability and long term durability of the battery packs in pure and extended range electric vehicles. Unfortunately, too many of these analyses begin with “I am not an engineer, but…”  So it was refreshing to read the objective scientific analysis of the Tesla Roadster battery pack published recently by Plug In America. The highlights of this report are:

  • The capacity of the battery pack after 5 years and 50,000 miles is expected to be 80-85% of the original, an average loss of about 3.7 miles (1.6%) per 10,000 miles driven. This is better performance than Tesla’s promised estimate of 70% of the original capacity. However, the study found considerable variation among vehicles with similar mileage.
  • The study found no apparent deterioration in capacity over vehicle’s age, although the oldest data was 4.5 years old (The Roadster production ended in 2012).
  • The studied did not detect an effect of hot climate on the battery’s cell life. Tesla’s thermal management system, which is designed primarily to ensure performance in cold weather, also helps protect the system from very high operating temperatures.

Plug In America also publsihed a similar analysis of the Nissan Leaf battery pack.

 

The Vital Few And The Trivial Many

By Manufacturing 2 Comments

A Tribute to Pareto, Juran, and the 80/20 Rule

The “80/20 rule” has become ubiquitous in everyday business language. This rule, or rather an axiom, states that roughly 80% of the effects come from 20% of the causes. For instance, we might say that 20% of the employees do 80% of the work, or 20% of the quality problems account for 80% of the scrap. Many refer to the 80/20 rule as “Pareto’s Law.”

Vilfredo Pareto

Vilfredo Pareto (1848-1923)

Vilfredo Pareto (1848–1923) was an Italian social-economist who argued that people are physically, intellectually and morally unequal. Pareto maintained that in society as a whole, and in any of its classes and subgroups, some people are more capable than others. The most gifted in any grouping form the “elite” of that group.

Pareto’s original use of the term “elite” did not mean specific social connotation; it simply denotes “a class of the people who have the highest indices in their branch of activity.” He divides the elite class into two classes: “a governing elite, comprising individuals who directly or indirectly play some considerable part in government, and a non-governing elite, comprising the rest.” According to Pareto, society has a tendency to maintain equilibrium, and people are entering and leaving the elite to maintain the natural balance.

Pareto is best known for his “Pareto’s Principle” of income distribution. He found that about 20% of the wealthiest people in Italy owned 80% of the land, which led him to conclude that in all countries and times, the distribution of wealth follows a similar pattern. Indeed, if we total the GDP of the world’s richest countries, we find that 20% of the world’s wealthiest people control nearly 90% of the wealth.

Joseph Juran (1904–2008)

Joseph Juran (1904–2008)

Quality management pioneer Joseph Juran (1904–2008) recognized a universal principle he called the “vital few and trivial many”: 20% of the causes are responsible for 80% of the results. In his 1950 article “Pareto, Lorenz, Cournot, Bernoulli, Juran and Others“, which appeared in the book Critical Evaluations in Business and Management, Juran incorrectly applied Pareto’s socio-economic observations to this broader observation and named it Pareto’s Principle.

In 1974, Juran published an article titled “The Non-Pareto Principle; Mea Culpa“, in which he wrote:

The “Pareto principle” has by this time become deeply rooted in our industrial literature. It is a shorthand name for the phenomenon that in any population which contributes to a common effect, a relative few of the contributors account for the bulk of the effect.

Years ago I gave the name “Pareto” to this principle of the “vital few and trivial many.” On subsequent challenge, I was forced to confess that I had mistakenly applied the wrong name to the principle. This confession changed nothing – the name “Pareto principle” has continued in force, and seems destined to become a permanent label for the phenomenon.

The matter has not stopped with my own error. On various occasions, contemporary authors, when referring to the Pareto principle, have fabricated some embellishments and otherwise attributed to Vilfredo Pareto additional things which he did not do. My motive in offering the present paper is in part to minimize this tendency to embroider the work of a distinguished Italian economist. In addition, I have for some time felt an urge to narrate just how it came about that some early experiences in seemingly unrelated fields (quality control, cryptanalysis, industrial engineering, government administration, management research) nevertheless converged to misname the Pareto principle.

As Juran wrote, the incorrect name of the principle does not change the validity of the notion the vital few and trivial many. Focus your attention on the few vital elements in your business that promise the most important result, and avoid the common trap of trying to improve issues that may be very visible but improving them will have only an inconsequential effect. This might be a good lesson for some Six Sigma zealots: Not every highly variability process is worth attenuating.

Design For Excellence: How Manufacturers Reduce Costly Design Mistakes

By Manufacturing 6 Comments

QualityIn the course of designing and manufacturing new products, engineers often make costly design mistakes. They do not design the correct functionality, choose components that do not meet reliability requirements, create designs that are difficult to manufacture and service, and, in effort to correct these mistakes, they often miss time and budget expectations.

Good PDP (product development process) practices dictate that design and manufacturability mistakes are to be captured during design reviews, prototyping and early manufacturing runs. Still, too many errors aren’t identified and corrected in time, before the product is shipped, as is frequently made evident by poor product quality, high rate of warranty claims and product recalls, and expensive repair services.

My work with several manufacturing companies shows that many design mistakes are completely avoidable, and as many could have been discovered and rectified before they resulted in manufacturing problems and product failures, forced massive recalls, and tarnished the brand’s image. For example, a high tech manufacturer redesigned a plastic enclosure to improve airflow. However, the design change led to reduction in the thickness of one of the enclosure’s walls, which, in turn, produced high rate of defective enclosures during manufacturing, and subpar quality of fielded units.

The important point in this story is that the theory and practice of plastic molding is well understood, and mistakes such as inadequate wall thickness or neglecting to include support ribs should happen only infrequently, or, at least, be detected and rectified early in product development, before volume manufacturing, reducing the cost of scrap and retooling, and improving overall productivity of engineers that should focus on innovation and design rather than on managing engineering changes to correct avoidable design errors.

There are many reasons why designers make such obvious errors. In an environment where demand for faster time to market under reduced budgets and lean resources dictates rapid cadence of innovation, such error are easy to miss. And we should assume that these pressures will not ease any time soon; quite the opposite. As design complexity and the use of new material and processes continue to increase in order to stay competitive, so will the strain to accelerate innovation and time to market. Moreover, the aging of the experienced workforce is resulting in gradual attrition in practical design and manufacturing knowledge that is not easily replaceable by the low supply of well-educated yet inexperienced design and manufacturing engineers.

There are, of course, many manufacturing companies that are taking active steps to reduce the occurrences of avoidable costly mistakes. Working with these companies, I have identified the 5 key areas successful companies excel in:

  • Frontload Decisions. This is an old advice that is still as relevant as it has ever been. All product lifecycle related considerations, including manufacturability (as we discussed earlier), supply chain, service and product end of life should be evaluated and optimized early in the design. PDP practices are typically implemented as a linear forward-feeding process, which can delay critical decisions concerning downstream activities, such as manufacturability and maintainability. Good product lifecycle management practices brings all requirements and constraints, which often can be in conflict – for instance, the airflow vs. manufacturability example I presented earlier – and reach an optimal solution. I often refer to this as DFX: Design for Multidisciplinary Constraints, or, if you prefer: Design for Excellence.
  • Standardize Designs and Processes; Maximize Reuse. One of the bigger challenges I encounter in many companies is the insatiable urge to innovate, to come up with new designs, to do things differently. These are all important traits. At the same time, smart companies are careful not to innovate for innovation sake. When practical, these companies make sure to standardize design elements and manufacturing processes so that they can avoid repeating mistakes of the past, and when errors do occur, they can be identified and corrected swiftly.
  • Implement Best Practices. This is an easy advice to follow, yet not many do. Engineering, Manufacturing, Quality, and practically everyone in your product team has perspective and experience that might be worth incorporating in design guidelines throughout the product lifecycle.
  • Unify Methods and Tools. The complexity and multidisciplinary nature of product design today demands the use of several design and analysis tools to help product engineers assess the design from multiple perspectives simultaneously: functionality, cost, reliability, manufacturability, serviceability and several others. These should be synthesized into a single decision-making framework to create a complete, accurate and up to date context for higher-fidelity design decisions. By implementing a formal DFX workbench and applying complex multidisciplinary design rules objectively and consistently, companies are able to make better design trade-off decisions, identify opportunities for design reuse, apply best practices, and improve engineering productivity.
  • Maximize Communication and Collaboration. The multidisciplinary nature of product design and the increasingly elongated and often fragmented design and supply chains strain product companies. Effective collaboration in product design, manufacturing and quality management are critical. Here, again, a unified framework for encapsulating best practices, both formal and informal, can help to create an effective and agile design
    and manufacturing environment.

Obviously, different companies take different approaches and use different tools to accomplish these objectives, but it appears that independent of the tools, companies implementing a structured approach to DFX realize similar benefits:

  • Reduce the time and cost required to achieve quality targets
  • Reduce the number of design and prototyping iterations
  • Achieve faster time to market
  • Reduce occurrences and impact of manufacturing line downtime
  • Reduce manual effort handling quality spills

One such manufacturing company that I studied conducted a detailed benefits analysis of its DFX implementation and reported the following results:

  • 20% reduction in cycle time
  • 50% reduction in station space
  • 92% reduction in line downtime
  • 52% reduction in scrap